Serving queries to multi-resolution datasets on disk-based storage clusters

Xi Zhang; Tony Pan; Umit Catalyurek; Tahsin Kurc; Joel Saltz

Serving queries to multi-resolution datasets on disk-based storage clusters

Xi Zhang
, Tony Pan
, Umit Catalyurek
, Tahsin Kurc
, Joel Saltz

Biomedical Informatics

Ohio State University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

3 Scopus citations

Abstract

This paper is concerned with efficient querying of very large multi-resolution datasets on storage and compute clusters. We present a suite of services that support storage, indexing, and data processing (data sampling and data aggregation) on datasets that consist of a collection of multiresolution grids. We empirically evaluate the performance impact of different data declustering, indexing, and query processing strategies. The experimental evaluation is carried out using a data server implemented to serve multiterabyte multi-resolution volumetric datasets to remote visualization clients and a one-terabyte multi-resolution volumetric dataset on a PC cluster with distributed disk space.

Original language	English
Title of host publication	2004 IEEE International Symposium on Cluster Computing and the Grid, CCGrid 2004
Pages	490-498
Number of pages	9
State	Published - 2004
Event	2004 IEEE International Symposium on Cluster Computing and the Grid, CCGrid 2004 - Chicago, IL, United States Duration: Apr 19 2004 → Apr 22 2004

Publication series

Name	2004 IEEE International Symposium on Cluster Computing and the Grid, CCGrid 2004

Conference

Conference	2004 IEEE International Symposium on Cluster Computing and the Grid, CCGrid 2004
Country/Territory	United States
City	Chicago, IL
Period	04/19/04 → 04/22/04

Cite this

@inproceedings{e9845b388df54fa6b7498c3012c3a24b,

title = "Serving queries to multi-resolution datasets on disk-based storage clusters",

abstract = "This paper is concerned with efficient querying of very large multi-resolution datasets on storage and compute clusters. We present a suite of services that support storage, indexing, and data processing (data sampling and data aggregation) on datasets that consist of a collection of multiresolution grids. We empirically evaluate the performance impact of different data declustering, indexing, and query processing strategies. The experimental evaluation is carried out using a data server implemented to serve multiterabyte multi-resolution volumetric datasets to remote visualization clients and a one-terabyte multi-resolution volumetric dataset on a PC cluster with distributed disk space.",

author = "Xi Zhang and Tony Pan and Umit Catalyurek and Tahsin Kurc and Joel Saltz",

year = "2004",

language = "English",

isbn = "078038430X",

series = "2004 IEEE International Symposium on Cluster Computing and the Grid, CCGrid 2004",

pages = "490--498",

booktitle = "2004 IEEE International Symposium on Cluster Computing and the Grid, CCGrid 2004",

note = "2004 IEEE International Symposium on Cluster Computing and the Grid, CCGrid 2004 ; Conference date: 19-04-2004 Through 22-04-2004",

}

Zhang, X, Pan, T, Catalyurek, U, Kurc, T & Saltz, J 2004, Serving queries to multi-resolution datasets on disk-based storage clusters. in 2004 IEEE International Symposium on Cluster Computing and the Grid, CCGrid 2004. 2004 IEEE International Symposium on Cluster Computing and the Grid, CCGrid 2004, pp. 490-498, 2004 IEEE International Symposium on Cluster Computing and the Grid, CCGrid 2004, Chicago, IL, United States, 04/19/04.

Serving queries to multi-resolution datasets on disk-based storage clusters. / Zhang, Xi; Pan, Tony; Catalyurek, Umit et al.
2004 IEEE International Symposium on Cluster Computing and the Grid, CCGrid 2004. 2004. p. 490-498 (2004 IEEE International Symposium on Cluster Computing and the Grid, CCGrid 2004).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Serving queries to multi-resolution datasets on disk-based storage clusters

AU - Zhang, Xi

AU - Pan, Tony

AU - Catalyurek, Umit

AU - Kurc, Tahsin

AU - Saltz, Joel

PY - 2004

Y1 - 2004

N2 - This paper is concerned with efficient querying of very large multi-resolution datasets on storage and compute clusters. We present a suite of services that support storage, indexing, and data processing (data sampling and data aggregation) on datasets that consist of a collection of multiresolution grids. We empirically evaluate the performance impact of different data declustering, indexing, and query processing strategies. The experimental evaluation is carried out using a data server implemented to serve multiterabyte multi-resolution volumetric datasets to remote visualization clients and a one-terabyte multi-resolution volumetric dataset on a PC cluster with distributed disk space.

AB - This paper is concerned with efficient querying of very large multi-resolution datasets on storage and compute clusters. We present a suite of services that support storage, indexing, and data processing (data sampling and data aggregation) on datasets that consist of a collection of multiresolution grids. We empirically evaluate the performance impact of different data declustering, indexing, and query processing strategies. The experimental evaluation is carried out using a data server implemented to serve multiterabyte multi-resolution volumetric datasets to remote visualization clients and a one-terabyte multi-resolution volumetric dataset on a PC cluster with distributed disk space.

UR - https://www.scopus.com/pages/publications/4544299732

M3 - Conference contribution

AN - SCOPUS:4544299732

SN - 078038430X

SN - 9780780384309

T3 - 2004 IEEE International Symposium on Cluster Computing and the Grid, CCGrid 2004

SP - 490

EP - 498

BT - 2004 IEEE International Symposium on Cluster Computing and the Grid, CCGrid 2004

T2 - 2004 IEEE International Symposium on Cluster Computing and the Grid, CCGrid 2004

Y2 - 19 April 2004 through 22 April 2004

ER -

Serving queries to multi-resolution datasets on disk-based storage clusters

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